A comprehensive utility function for resource allocation in mobile edge computing

作     者：Ali, Zaiwar Khaf, Sadia Abbas, Ziaul Haq Abbas, Ghulam Jiao, Lei Irshad, Amna Kwak, Kyung Sup Bilal, Muhammad 

作者机构：Research Laboratory GIK Institute of Engineering Sciences and Technology Topi23640 Pakistan Faculty of Electrical Engineering GIK Institute of Engineering Sciences and Technology Topi23640 Pakistan Faculty of Computer Sciences and Engineering GIK Institute of Engineering Sciences and Technology Topi23640 Pakistan  Grimstad4898 Norway Department of Information and Communication Engineering Inha University Incheon22212 Korea Republic of Department of Computer and Electronics Systems Engineering Hankuk University of Foreign Studies Gyeonggi-do17035 Korea Republic of 

出 版 物：《arXiv》 (arXiv)

年 卷 期：2020年

核心收录：

主　　题：Mobile edge computing 

摘      要：In mobile edge computing (MEC), one of the important challenges is how much resources of which mobile edge server (MES) should be allocated to which user equipment (UE). The existing resource allocation schemes only consider CPU as the requested resource and assume utility for MESs as either a random variable or dependent on the requested CPU only. This paper presents a novel comprehensive utility function for resource allocation in MEC. The utility function considers the heterogeneous nature of applications that a UE offloads to MES. The proposed utility function considers all important parameters, including CPU, RAM, hard disk space, required time, and distance, to calculate a more realistic utility value for MESs. Moreover, we improve upon some general algorithms, used for resource allocation in MEC and cloud computing, by considering our proposed utility function. We name the improved versions of these resource allocation schemes as comprehensive resource allocation schemes. The UE requests are modeled to represent the amount of resources requested by the UE as well as the time for which the UE has requested these resources. The utility function depends upon the UE requests and the distance between UEs and MES, and serves as a realistic means of comparison between different types of UE requests. Choosing (or selecting) an optimal MES with the optimal amount of resources to be allocated to each UE request is a challenging task. We show that MES resource allocation is sub-optimal if CPU is the only resource considered. By taking into account the other resources, i.e., RAM, disk space, request time, and distance in the utility function, we demonstrate improvement in the resource allocation algorithms in terms of service rate, utility, and MES energy *** Codes 46Fxx © 2020, CC BY.